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Q&A with Suplari: Businesses want ‘a more procurement-focused approach to data analytics’

Spend analytics these days offer an array of insights into the data that’s increasingly being collected, but it’s not easy for businesses to know which solution to select or whether to go with a suite provider that requires a vast overhaul of a company’s departments and processes.

In two articles, we’ve explored how to weigh a best-of-breed spend analytics module versus an end-to-end solution implementation, and we’ve looked at what it takes to prepare a business to get the most out of its spend analytics solution.

To learn more about the issues, we talked with Jake Arnold, the Head of Customer Success at Suplari, whose solution is an AI-driven spend analytics platform to help enterprise companies drive financial performance.


Spend Matters: How should a business evaluate a best-of-breed spend analytics offering like Suplari’s when it’s also considering a suite of procurement technology?

Jake Arnold: For many of our customers, the question is not a matter of this offering versus that one, it’s which best-of-breed offering will best enhance our current or future suite (S2P, P2P, etc.). Our customers understand that most full suite software offerings will give them a more sustainable and compliance-based process around their spending and spend-related procedures. However, they still find the need for a more procurement-focused approach to data analytics.

Spend analytics help businesses plan for the future, whereas old spend analysis methods like a spend cube measured only what was already spent. What technology is driving the advances that allow for that forward-looking ability?

The trend, and the dream of many procurement professionals, is to have artificial intelligence or machine learning look for patterns in the data sources to help predict or flag potential spend or supplier impacts — like alerting category managers to unusually high spend with a non-preferred supplier in a risky spend area, predicting price increases based on tariff or commodity trends, helping to determine the area of spend that will give the highest return on a negotiation or RFP, or even helping to predict a needed RFX based on a company’s spend trends. These are all time-consuming activities for procurement today, but the more intelligent data analytics become, the more procurement professionals can rely upon the opportunities provided to them.

With the massive amounts of new data being generated these days, how do you explain the tools and technology involved in gathering that data? Things like artificial intelligence and machine learning. What other concepts should be understood before procurement professionals launch their tech selection?

We all know the underlying problem of data is the age-old issue of “garbage in, garbage out” but part of the solution that new analytics tools can offer is an overall way to visualize the garbage and can even help connect disparate data sets to make more sense of the whole set of data. AI, algorithms, machine learning, all have a role to play when it comes to pulling and cleaning up data so that procurement can use a set of clean data to begin reviewing for their cyclical planning sessions. Reviewing P2P or best-in-breed analytics solutions should include a review of what types of data sets are needed to make decisions around corporate goals. Can the solution help increase diversity spending, help control rogue spending, help reveal tail spending patterns based on preferred suppliers, or help give a view into supplier performance or risk factors? For many of these answers, procurement teams need data that sit within many sources of truth. Knowing which solutions can give visibility to these areas should be a part of the decision-making process.

Do you have a favorite “a-ha” moment when a client finally sees all of the new insights that spend analytics unlocks?

Many, but what comes to mind are the meetings with high-level executives who are not typically looking at low-level spend data. We have many meetings where we see the C-suite in the room wants to dive deeper and deeper into an insight after they see something interesting. It’s exciting to see the energy and interest from them, but I always cringe at the idea of all the work their interest will cause the whole team post-meeting.

What is the next step for spend analytics? What’s on Suplari’s roadmap?

Suplari will continue to develop our insights engine to deliver more complex and predictive insights, but we also want to enable procurement teams to be able to better organize their team’s activities more effectively. Suplari wants to simplify the process of identifying opportunities, collaborating with budget or stakeholders, and present the resulting impact to the business in an easy to understand way. Suplari will also continue to develop better ways to clean and review data by applying AI methods to categorization, supplier normalization and spend forecasting. Overall, we want to take the mystery out of a company’s spend and financial information and put it into the hands of those who can make an impact to that spend.

This Brand Studio article was written with Suplari.